{
 "cells": [
  {
   "cell_type": "markdown",
   "source": [
    "4.1Matplotlib常用技巧  \n",
    "4.1.1 导入Matplotlib  \n",
    "4.1.2 设置绘图样式  \n",
    "4.1.3 用不用show()？如何显示图形  \n",
    "如果数据可视化图不能被看见，那就一点儿用也没有了。但如何显示你的图形，就取决于具体的开发环境了。Matplotlib的最佳实践与你使用的开发环境有关。简单来说，就是有三种开发环境，分别是脚本、IPython shell和IPython Notebook。  \n",
    "1. 在脚本中画图  \n",
    "如果你在一个脚本文件中使用Matplotlib，那么显示图形的时候必须使用plt.show()。plt.show()会启动一个事件循环（event loop），并找到所有当前可用的图形对象，然后打开一个或多个交互式窗口显示图形。  "
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "source": [
    "import matplotlib.pyplot as plt \n",
    "import numpy as np \n",
    "x = np.linspace(0, 10, 100) \n",
    "plt.plot(x, np.sin(x)) \n",
    "plt.plot(x, np.cos(x)) \n",
    "plt.show()"
   ],
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "不过有一点需要注意，一个Python会话（session）中只能使用一次plt.show()，因此通常都把它放在脚本的最后。多个plt.show()命令会导致难以预料的显示异常，应该尽量避免。"
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "2. 在IPython shell中画图  \n",
    "在IPython启动Matplotlib模式就可以使用它"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "source": [
    "%matplotlib\n",
    "import matplotlib.pyplot as plt"
   ],
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Using matplotlib backend: TkAgg\n"
     ]
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "此后的任何plt命令都会自动打开一个图形窗口，增加新的命令，图形就会更新。有一些变化（例如改变已经画好的线条属性）不会自动及时更新；对于这些变化，可以使用plt.draw()强制更新。在IPython  shell中启动Matplotlib模式之后，就不需要使用plt.show()了。\n",
    "3. 在IPython Notebook中画图  \n",
    "用IPython Notebook进行交互式画图与使用IPython shell类似，也需要使用%matplotlib命令。你可以将图形直接嵌在IPython Notebook页面中，有两种展现形式。\n",
    "• %matplotlib notebook会在Notebook中启动交互式图形。  \n",
    "• %matplotlib inline会在Notebook中启动静态图形  "
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "source": [
    "%matplotlib inline\n",
    "import numpy as np        \n",
    "x = np.linspace(0, 10, 100)\n",
    "fig = plt.figure()        \n",
    "plt.plot(x, np.sin(x), '-')        \n",
    "plt.plot(x, np.cos(x), '--')"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fdad17dbca0>]"
      ]
     },
     "metadata": {},
     "execution_count": 6
    },
    {
     "output_type": "display_data",
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "4.1.4 将图形保存为文件   \n",
    "Matplotlib的一个优点是能够将图形保存为各种不同的数据格式。你可以用savefig()命令将图形保存为文件。例如，如果要将图形保存为PNG格式，你可以运行这行代码：  \n"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [
    "fig.savefig('my_figure.png')"
   ],
   "outputs": [],
   "metadata": {}
  },
  {
   "cell_type": "markdown",
   "source": [
    "为了确定文件中是否保存有我们需要的内容，可以用IPython的Image对象来显示文件内容（如图4-2所示）：In[7]: from IPython.display import Image        Image('my_figure.png')图4-2：渲染PNG基本图形\n"
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "source": [
    "fig.canvas.get_supported_filetypes()"
   ],
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "{'eps': 'Encapsulated Postscript',\n",
       " 'jpg': 'Joint Photographic Experts Group',\n",
       " 'jpeg': 'Joint Photographic Experts Group',\n",
       " 'pdf': 'Portable Document Format',\n",
       " 'pgf': 'PGF code for LaTeX',\n",
       " 'png': 'Portable Network Graphics',\n",
       " 'ps': 'Postscript',\n",
       " 'raw': 'Raw RGBA bitmap',\n",
       " 'rgba': 'Raw RGBA bitmap',\n",
       " 'svg': 'Scalable Vector Graphics',\n",
       " 'svgz': 'Scalable Vector Graphics',\n",
       " 'tif': 'Tagged Image File Format',\n",
       " 'tiff': 'Tagged Image File Format'}"
      ]
     },
     "metadata": {},
     "execution_count": 7
    }
   ],
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "source": [],
   "outputs": [],
   "metadata": {}
  }
 ],
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  "orig_nbformat": 4,
  "language_info": {
   "name": "python",
   "version": "3.8.10",
   "mimetype": "text/x-python",
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "pygments_lexer": "ipython3",
   "nbconvert_exporter": "python",
   "file_extension": ".py"
  },
  "kernelspec": {
   "name": "python3",
   "display_name": "Python 3.8.10 64-bit ('d2l-zh': conda)"
  },
  "interpreter": {
   "hash": "0bedf3452ed48e38a2b75ff9f66ce8ae9ae2e92e8665cb618ee0797d2f46b9e5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}